MaziyarPanahi commited on
Commit
d02b0d1
1 Parent(s): 340a6dd

Update app.py (#1)

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Files changed (1) hide show
  1. app.py +18 -7
app.py CHANGED
@@ -1,5 +1,8 @@
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  import gradio as gr
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- from transformers import LlavaNextProcessor, LlavaNextForConditionalGeneration, TextIteratorStreamer
 
 
 
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  from threading import Thread
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  import re
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  import time
@@ -7,9 +10,17 @@ from PIL import Image
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  import torch
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  import spaces
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- processor = LlavaNextProcessor.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf")
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- model = LlavaNextForConditionalGeneration.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf", torch_dtype=torch.float16, low_cpu_mem_usage=True)
 
 
 
 
 
 
 
 
 
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  model.to("cuda:0")
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  @spaces.GPU
@@ -26,7 +37,7 @@ def bot_streaming(message, history):
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  if image is None:
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  gr.Error("You need to upload an image for LLaVA to work.")
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- prompt=f"[INST] <image>\n{message['text']} [/INST]"
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  image = Image.open(image).convert("RGB")
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  inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
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@@ -37,7 +48,7 @@ def bot_streaming(message, history):
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  thread = Thread(target=model.generate, kwargs=generation_kwargs)
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  thread.start()
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- text_prompt =f"[INST] \n{message['text']} [/INST]"
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  buffer = ""
@@ -50,8 +61,8 @@ def bot_streaming(message, history):
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  yield generated_text_without_prompt
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- demo = gr.ChatInterface(fn=bot_streaming, title="LLaVA NeXT", examples=[{"text": "What is on the flower?", "files":["./bee.jpg"]},
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  {"text": "How to make this pastry?", "files":["./baklava.png"]}],
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- description="Try [LLaVA NeXT](https://huggingface.co/docs/transformers/main/en/model_doc/llava_next) in this demo (more specifically, the [Mistral-7B variant](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf)). Upload an image and start chatting about it, or simply try one of the examples below. If you don't upload an image, you will receive an error.",
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  stop_btn="Stop Generation", multimodal=True)
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  demo.launch(debug=True)
 
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  import gradio as gr
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+
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+ from transformers import AutoProcessor, LlavaForConditionalGeneration
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+ from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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+
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  from threading import Thread
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  import re
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  import time
 
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  import torch
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  import spaces
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+ model_id = "xtuner/llava-llama-3-8b-v1_1-transformers"
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+
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+ processor = AutoProcessor.from_pretrained(model_id)
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+
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+ model = LlavaForConditionalGeneration.from_pretrained(
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+ model_id,
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+ torch_dtype=torch.float16,
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+ low_cpu_mem_usage=True,
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+ )
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+
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  model.to("cuda:0")
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  @spaces.GPU
 
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  if image is None:
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  gr.Error("You need to upload an image for LLaVA to work.")
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+ prompt=f"<|start_header_id|>user<|end_header_id|>\n\n<image>\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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  image = Image.open(image).convert("RGB")
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  inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
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  thread = Thread(target=model.generate, kwargs=generation_kwargs)
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  thread.start()
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+ text_prompt =f"<|start_header_id|>user<|end_header_id|>\n\n{message['text']}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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  buffer = ""
 
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  yield generated_text_without_prompt
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+ demo = gr.ChatInterface(fn=bot_streaming, title="LLaVA Llama-3-8B", examples=[{"text": "What is on the flower?", "files":["./bee.jpg"]},
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  {"text": "How to make this pastry?", "files":["./baklava.png"]}],
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+ description="Try [LLaVA Llama-3-8B](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-transformers). Upload an image and start chatting about it, or simply try one of the examples below. If you don't upload an image, you will receive an error.",
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  stop_btn="Stop Generation", multimodal=True)
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  demo.launch(debug=True)